Efficacy of Ivabradine in Combination with Beta-Blockers Versus Uptitration of Beta-Blockers in Patients with Stable Angina (CONTROL-2 Study)
Bibliographic record
Abstract
INTRODUCTION: Heart rate (HR) reduction is an integral part of antianginal therapy, but many patients do not reach the guideline-recommended target of less than 60 bpm despite high use of beta-blockers (BB). Failure to uptitrate BB doses may be partly to blame. To explore other options for lowering HR and improving angina control, CONTROL-2 was initiated to compare the efficacy and tolerability of the combination of BBs with ivabradine versus uptitration of BBs to maximal tolerated dose, in patients with stable angina. METHODS: This multicenter, open, randomized study included 1104 patients with Canadian Cardiovascular Society (CCS) class II or III stable angina, in sinus rhythm, and on background stable treatment with non-maximal recommended doses of BBs. Consecutive patients were allocated to ivabradine + BB or BB uptitration in a 4:1 ratio. RESULTS: At the end of the study (week 16), addition of ivabradine to BB treatment and BB uptitration resulted in reduction in HR (61 ± 6 vs. 63 ± 8 bpm; p = 0.001). At week 16, significantly more patients on ivabradine + BB were in CCS class I than with BB uptitration (37.1% vs. 28%; p = 0.017) and significantly more patients were angina-free (50.6% vs. 34.2%; p < 0.001). Patient health status based on the visual analogue scale (VAS) was also better in the ivabradine + BB group. Adverse events (AEs) were significantly more common with BB uptitration than with the ivabradine + BB combination (18.4% vs. 9.4%, p < 0.001). CONCLUSION: In patients with stable angina, combination therapy with ivabradine + BB demonstrated good tolerability, safety, and more pronounced clinical improvement, compared to BB uptitration. TRIAL REGISTRATION: ISRCTN30654443. FUNDING: Servier.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".